CN117710908A - Vehicle identification system and method, storage medium and electronic device - Google Patents
Vehicle identification system and method, storage medium and electronic device Download PDFInfo
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Abstract
The application discloses a vehicle identification system and method, a storage medium and an electronic device, wherein the system comprises: the headstock identification intelligent box is connected with the N first camera devices and is used for analyzing video streams acquired by the N first camera devices to determine headstock identification results corresponding to the video streams acquired by the N first camera devices; the vehicle type recognition intelligent box is connected with the M second camera devices and is used for analyzing video streams collected by the M second camera devices to determine vehicle type recognition results corresponding to the video streams collected by the M second camera devices; n and M are positive integers, N is greater than 1, and the video stream at least comprises image information of two vehicles; the intelligent vehicle type recognition box is also used for determining a vehicle recognition result according to the vehicle head recognition result and the vehicle type recognition result. By adopting the technical scheme, the technical problem of low efficiency and accuracy in identifying the multi-lane vehicle type information is solved.
Description
Technical Field
The application relates to the technical field of intelligent transportation, in particular to a vehicle identification system and method, a storage medium and an electronic device.
Background
At present, a single box performance and software design limit of a vehicle type identification intelligent box is that a plurality of cameras on a portal frame of a road can be accessed only with one camera for vehicle body identification and one camera for vehicle head information identification, the utilization rate of the plurality of cameras of the portal frame is limited, and vehicle head data of a single lane can be identified only when the vehicle is in a plurality of lanes of the road, and the efficiency and accuracy of identification are reduced when the traffic flow of the lane is large due to the performance limit of the single intelligent box.
Aiming at the technical problems of low recognition efficiency and low recognition accuracy of multi-lane vehicle type information in the related art, no effective solution is proposed yet.
Disclosure of Invention
The embodiment of the application provides a vehicle identification system and method, a storage medium and an electronic device, which are used for at least solving the technical problems of low efficiency and accuracy in identifying multi-lane vehicle type information in the related technology.
According to one embodiment of the present application, there is provided a vehicle identification system including: the headstock identification intelligent box is connected with the N first camera devices and is used for analyzing the video streams collected by the N first camera devices to determine headstock identification results corresponding to the video streams collected by the N first camera devices; the vehicle type recognition intelligent box is connected with the M second camera devices and is used for analyzing video streams collected by the M second camera devices to determine vehicle type recognition results corresponding to the video streams collected by the M second camera devices; n and M are positive integers, N is greater than 1, and the video stream at least comprises image information of two vehicles; the intelligent vehicle type recognition box is further used for determining a vehicle recognition result according to the vehicle head recognition result and the vehicle type recognition result.
In one exemplary embodiment, the M is equal to 1, and the vehicle type recognition smart box includes: the side camera service module is used for extracting a video stream corresponding to the vehicle body data acquired by the second camera equipment for analysis.
In one exemplary embodiment, the vehicle model identification intelligence further comprises: the version identification module is used for adding a mark variable to the virtual machine application corresponding to the vehicle type identification intelligent, wherein the mark variable is used for identifying the version type of the current vehicle type identification intelligent.
In one exemplary embodiment, the vehicle model identification intelligence further comprises: and the compatible module is connected with the version identification module and is used for controlling the virtual machine application to run the application function corresponding to the version type under the condition that the version type of the vehicle type identification intelligent is determined.
In one exemplary embodiment, the head recognition smart box includes: the network service module is used for respectively setting network channels for N first camera devices connected with the headstock identification intelligent box.
In an exemplary embodiment, the head recognition smart box further includes: and the analyzer module is connected with the network service module and used for carrying out task distribution control on the N first camera devices, wherein the task distribution control is used for analyzing N video streams of the N first camera devices transmitted through the network channel and distributing corresponding target analyzers for each video stream in the N video streams so as to simultaneously analyze the N video streams through the N target analyzers.
In one exemplary embodiment, the vehicle model identification intelligence further comprises: the buffer memory module is connected with the virtual machine application corresponding to the vehicle type recognition intelligent and is used for storing vehicle type analysis data generated in the virtual machine and receiving and storing vehicle head analysis data transmitted by the vehicle head recognition intelligent box through network connection; and the fusion module is connected with the cache module and used for fusing the vehicle model analysis data and the vehicle head analysis data stored in the cache module to obtain final data of vehicle body and vehicle head configuration.
According to another embodiment of the embodiments of the present application, there is also provided a vehicle identification method, including: analyzing video streams collected by N connected first camera devices through a head recognition intelligent box, and determining head recognition results corresponding to the video streams collected by the N first camera devices; analyzing video streams collected by M connected second camera devices through a vehicle type recognition intelligent box, and determining vehicle type recognition results corresponding to the video streams collected by the M second camera devices; n and M are positive integers, N is greater than 1, and the video stream at least comprises image information of two vehicles; and determining a vehicle recognition result according to the vehicle head recognition result and the vehicle type recognition result.
According to yet another aspect of the embodiments of the present application, there is also provided a computer-readable storage medium having a computer program stored therein, wherein the computer program is configured to perform the above-described vehicle identification method when run.
According to still another aspect of the embodiments of the present application, there is further provided an electronic device including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the vehicle identification method described above through the computer program.
In the embodiment of the application, the headstock identification intelligent box is connected with N first camera devices and is used for analyzing video streams acquired by the N first camera devices to determine headstock identification results corresponding to the video streams acquired by the N first camera devices; the vehicle type recognition intelligent box is connected with the M second camera devices and is used for analyzing video streams collected by the M second camera devices to determine vehicle type recognition results corresponding to the video streams collected by the M second camera devices; n and M are positive integers, N is greater than 1, and the video stream at least comprises image information of two vehicles; in addition, the vehicle recognition result can be determined on the basis of the vehicle head recognition result and the vehicle type recognition result through the vehicle type recognition intelligent box. By adopting the technical scheme, the technical problem that the efficiency and accuracy of identifying the multi-lane vehicle type information are low is solved, and the efficiency and accuracy of identifying the multi-lane vehicle type information are improved.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic diagram of a hardware environment of a vehicle identification method according to an embodiment of the present application;
FIG. 2 is a block diagram of a vehicle identification system according to an embodiment of the present application;
FIG. 3 is a software interaction schematic of a vehicle model identification smart box according to an embodiment of the present application;
FIG. 4 is a schematic diagram of software interactions of a vehicle model identification smart box and a vehicle head identification smart box according to an embodiment of the present application;
FIG. 5 is a flow chart of a vehicle identification method according to an embodiment of the present application;
fig. 6 is an electronic device for implementing the above-described vehicle charge and discharge management method according to an embodiment of the present application.
Detailed Description
In order to make the present application solution better understood by those skilled in the art, the following description will be made in detail and with reference to the accompanying drawings in the embodiments of the present application, it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, subsystem, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements that are expressly listed or inherent to such process, method, article, or apparatus.
According to one aspect of an embodiment of the present application, a vehicle identification method is provided. The vehicle identification method is widely applied to software system operation and other scenes. Alternatively, in the present embodiment, the above-described vehicle identification method may be applied to a hardware environment constituted by the terminal device 102 and the server 104 as shown in fig. 1. As shown in fig. 1, the server 104 is connected to the terminal device 102 through a network, and may be used to provide services (such as application services and the like) for a terminal or a client installed on the terminal, a database may be set on the server or independent of the server, for providing data storage services for the server 104, and cloud computing and/or edge computing services may be configured on the server or independent of the server, for providing data computing services for the server 104.
The network may include, but is not limited to, at least one of: wired network, wireless network. The wired network may include, but is not limited to, at least one of: a wide area network, a metropolitan area network, a local area network, and the wireless network may include, but is not limited to, at least one of: WIFI (Wireless Fidelity ), bluetooth. The terminal device 102 may not be limited to intelligent devices such as PCs, mobile phones, tablet computers, and engineering devices such as motors.
In this embodiment, a vehicle identification system is provided and applied to the server, and fig. 2 is a block diagram of a vehicle identification system according to an embodiment of the present application, where the system includes the following contents:
the headstock recognition intelligent box 22 is connected with the N first camera devices and is used for analyzing the video streams collected by the N first camera devices to determine headstock recognition results corresponding to the video streams collected by the N first camera devices;
the vehicle type recognition intelligent box 24 is connected with the M second camera devices, and is used for analyzing the video streams collected by the M second camera devices to determine vehicle type recognition results corresponding to the video streams collected by the M second camera devices, and determining vehicle recognition results according to the vehicle head recognition results and the vehicle type recognition results; n and M are positive integers, N is greater than 1, and the video stream at least comprises image information of two vehicles;
it should be noted that, the vehicle type recognition intelligent box 24 and the vehicle head recognition intelligent box 22 can cache the vehicle head recognition result and the vehicle type recognition result through the cache service preset in the vehicle type recognition intelligent box 24, so that the vehicle type recognition intelligent box can fuse the final data of matching the vehicle body and the vehicle head based on the cached data in the subsequent process.
Optionally, the head recognition smart box 22 may transmit the head recognition result to the vehicle type recognition smart box 24 through a network connection manner, where the network connection manner may be a wireless network or an effective network, and in this regard, the application is not limited too much.
Through the steps, the intelligent headstock recognition box is connected with N first camera devices and is used for analyzing video streams collected by the N first camera devices to determine headstock recognition results corresponding to the video streams collected by the N first camera devices; the vehicle type recognition intelligent box is connected with the M second camera devices and is used for analyzing video streams collected by the M second camera devices to determine vehicle type recognition results corresponding to the video streams collected by the M second camera devices; n and M are positive integers, N is greater than 1, and the video stream at least comprises image information of two vehicles; in addition, the vehicle recognition result can be determined on the basis of the vehicle head recognition result and the vehicle type recognition result through the vehicle type recognition intelligent box. By adopting the technical scheme, the technical problem that the efficiency and accuracy of identifying the multi-lane vehicle type information are low is solved, and the efficiency and accuracy of identifying the multi-lane vehicle type information are improved.
In one exemplary embodiment, the M is equal to 1, and the vehicle type recognition smart box includes: the side camera service module is used for extracting a video stream corresponding to the vehicle body data acquired by the second camera equipment for analysis.
In practical application, the intelligent box for vehicle type identification can process video stream through the following services: the side camera service (which is equivalent to the side camera service module) is mainly used for streaming and acquiring video stream data from the single-car body camera equipment; transmitting the acquired video stream data to an analyzer engine service for analysis, wherein the analyzer engine service is mainly used for providing an analysis function of a vehicle type recognition algorithm for a vehicle type recognition intelligent box; in addition, the side camera service can also issue device information to the vmr _lite service, wherein the vmr _lite service is mainly used for associating message forwarding and communication functions among various services in the vehicle type recognition intelligent box, so that the accuracy of data is ensured. Further, when the analyzer engine service completes the analysis, the corresponding recognition result is also reported to the vmr _lite service.
In one exemplary embodiment, the vehicle model identification intelligence further comprises: the version identification module is used for adding a mark variable to the virtual machine application corresponding to the vehicle type identification intelligent, wherein the mark variable is used for identifying the version type of the current vehicle type identification intelligent.
In one exemplary embodiment, the vehicle model identification intelligence further comprises: and the compatible module is connected with the version identification module and is used for controlling the virtual machine application to run the application function corresponding to the version type under the condition that the version type of the vehicle type identification intelligent is determined.
That is, in order to ensure compatibility with the old version smart box before, a flag variable can be added to the vmr _lite service to distinguish whether the old version of the vehicle type recognition box before or the new version of the vehicle type recognition box, so that the old version of the function can be compatible with the new version of the vehicle type recognition smart box, and the aim of accessing a vehicle head camera and a vehicle body camera in one smart box can be achieved.
In one exemplary embodiment, the head recognition smart box includes: the network service module is used for respectively setting network channels for N first camera devices connected with the headstock identification intelligent box.
It can be understood that by setting the corresponding network channels, different first camera devices can provide video streams for the head recognition intelligent box at the same time, and the head recognition intelligent box can also be controlled to receive the video stream state of each first camera device, so that the pull flow process is more flexible.
In an exemplary embodiment, the head recognition smart box further includes: and the analyzer module is connected with the network service module and used for carrying out task distribution control on the N first camera devices, wherein the task distribution control is used for analyzing N video streams of the N first camera devices transmitted through the network channel and distributing corresponding target analyzers for each video stream in the N video streams so as to simultaneously analyze the N video streams through the N target analyzers.
In an actual scene, a web service issues a vehicle head recognition task to vmr _lite, an analyzer acquires the issued recognition task from vmr _lite, the analyzer pulls a video stream of a camera through stream to analyze, after a result is detected, the recognition result is sent to a message queue provided by vmr _lite service, and the web service acquires the recognition result from the message queue of vmr _lite to classify and store.
In one exemplary embodiment, the vehicle model identification intelligence further comprises: the buffer memory module is connected with the virtual machine application corresponding to the vehicle type recognition intelligent and is used for storing vehicle type analysis data generated in the virtual machine and receiving and storing vehicle head analysis data transmitted by the vehicle head recognition intelligent box through network connection; and the fusion module is connected with the cache module and used for fusing the vehicle model analysis data and the vehicle head analysis data stored in the cache module to obtain final data of vehicle body and vehicle head configuration.
In order to better understand the process of the vehicle identification method, the following describes the flow of the implementation method of vehicle identification in combination with the alternative embodiment, but is not limited to the technical solution of the embodiment of the present application.
In this embodiment, a vehicle type recognition intelligent box for realizing vehicle recognition is provided, and the effect of being able to recognize a vehicle type is achieved in one intelligent box through the following interrelation of several services. As shown in fig. 3, fig. 3 is a schematic software interaction diagram of a vehicle type recognition smart box according to an embodiment of the present application; the method specifically comprises the following steps:
the analyzer engine service is mainly used for providing an analysis function of a vehicle type recognition algorithm for the vehicle type recognition intelligent box;
the stream service is mainly used for pulling video streams from the camera connected with the intelligent vehicle type recognition box;
the web service is used for sorting and classifying the final recognition result in the intelligent vehicle type recognition box and issuing algorithm tasks;
the system manager service is used for managing the bottom hardware and the operating system of the intelligent box;
vmr _lite service for associating message forwarding and communication functions between services in the vehicle type identification smart box.
Optionally, based on the multiple services, the whole process of issuing the recognition task to the output of the recognition result is that the web service issues the vehicle-mounted recognition task to vmr _lite, the analyzer obtains the issued recognition task from vmr _lite, the analyzer analyzes the video stream of the stream pull camera, after detecting the result, sends the recognition result to a message queue provided by vmr _lite service, and the web service obtains the recognition result from a message queue of vmr _lite, and classifies and stores the recognition result.
However, it should be noted that, in the above solution, because of the performance limitations of the vehicle type recognition smart box hardware and the single smart box, only one vehicle head camera can be connected to perform the limitation of vehicle information analysis of a single lane, and more cameras for vehicle head recognition cannot be connected to perform vehicle recognition at the same time.
As an optional implementation manner, in order to avoid the technical defects, a software design scheme capable of improving vehicle type recognition performance and recognition efficiency by expanding a vehicle head recognition intelligent box is provided, so that more cameras for vehicle head recognition are accessed, and efficiency and accuracy of recognition of multi-lane vehicle type information are improved.
It should be noted that, the above-mentioned extension scheme expands on the basis of original motorcycle type discernment intelligent box design to compatible original intelligent box's software function, and can expand out an independent locomotive information discernment intelligent box, in order to increase performance and recognition efficiency that whole motorcycle type discerned.
Optionally, fig. 4 is a schematic software interaction diagram of a vehicle type recognition smart box and a vehicle head recognition smart box according to an embodiment of the present application, and as shown in fig. 4, specific contents include the following: in order to expand the access to equipment and improve the performance of task analysis, an intelligent box special for identifying the head information is added, the head identification and the body identification are separated on different intelligent boxes, so that the performance pressure of a single box is reduced, more head cameras can be accessed for identifying the head information, the stream service in the original service of a vehicle type box is replaced, the video service is used, the video service is only used for accessing a single body camera and a single head camera for pulling a video stream, functions are fewer than those of the stream, the occupied box performance is less, meanwhile, in order to be compatible with a previous old version intelligent box, a flag variable is added in vmr _lite for distinguishing whether the previous old version of the vehicle type identification box or the new version of the vehicle type identification box, so that the functions of the old version can be compatible with the new version of the vehicle type identification intelligent box, and the functions of the new version of the vehicle type camera can be accessed in the intelligent box. In addition, web and analyzer services are adjusted on the basis of the software design of the original vehicle type recognition intelligent box in the separated vehicle type recognition intelligent box for vehicle type information recognition, so that the web and analyzer services can carry out control tasks on a plurality of cameras, the analyzer can analyze video streams of the cameras at the same time, and the recognized vehicle type information is transmitted to a cache of a Redis service of the vehicle type recognition intelligent box through network connection, so that the vehicle type recognition intelligent box can fuse final data matched with a vehicle body and a vehicle head based on the cached data.
In summary, according to the above-mentioned embodiments of the present invention, in the above original software design, in order to expand access to the device and improve performance of task analysis, a smart box dedicated to identifying the vehicle head information is added, the vehicle head identification and the vehicle body identification are separated on different smart boxes, so as to reduce performance pressure of a single box, and more vehicle head cameras can be accessed to identify the vehicle head information, stream services in original services of the vehicle type box are replaced, a side camera service is used, the side camera service is only used to access a single vehicle body camera and a single vehicle head camera to pull a video stream, functions are castrated compared with stream, occupied box performance is less, and in order to be compatible with a previous old version of the smart box, a flag variable is added in vmr _lite to distinguish whether the previous old version of the vehicle type identification box or the new version of the vehicle type identification box, so that functions of the old version can be compatible with the new version of the vehicle type identification box, and a vehicle head camera and a vehicle body camera can be accessed in the smart box. In addition, web and analyzer services are adjusted on the basis of the software design of the original vehicle type recognition intelligent box in the separated vehicle type recognition intelligent box for vehicle type information recognition, so that the web and analyzer services can carry out control tasks on a plurality of cameras, the analyzer can analyze video streams of the plurality of cameras at the same time, and the recognized vehicle type information is transmitted to a cache of a Redis service of the vehicle type recognition intelligent box through network connection so as to be used for merging final data matched with a vehicle body and a vehicle head based on the cached data of the vehicle type recognition intelligent box; the vehicle head recognition and the vehicle body recognition are separated, so that more vehicle head cameras can be connected, used equipment resources analyzed by the algorithm are split, the performance of the overall algorithm recognition is improved, the recognition efficiency of the original vehicle type recognition intelligent box can be improved, and the utilization rate of video resources of cameras on a road is also improved because more cameras can be connected.
From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method of the embodiments of the present application.
FIG. 5 is a flow chart of a vehicle identification method according to an embodiment of the present application; as shown in fig. 5, includes:
step S502, analyzing video streams collected by N connected first camera devices through a headstock identification intelligent box, and determining headstock identification results corresponding to the video streams collected by the N first camera devices;
step S504, analyzing video streams collected by the M connected second camera devices through a vehicle type recognition intelligent box, and determining vehicle type recognition results corresponding to the video streams collected by the M second camera devices; n and M are positive integers, N is greater than 1, and the video stream at least comprises image information of two vehicles;
and step S506, determining a vehicle recognition result according to the vehicle head recognition result and the vehicle type recognition result.
According to the method, the video streams collected by the N first camera devices connected with each other are analyzed through the headstock identification intelligent box, and headstock identification results corresponding to the video streams collected by the N first camera devices are determined; analyzing video streams collected by M connected second camera devices through a vehicle type recognition intelligent box, and determining vehicle type recognition results corresponding to the video streams collected by the M second camera devices; n and M are positive integers, N is greater than 1, and the video stream at least comprises image information of two vehicles; and determining a vehicle recognition result according to the vehicle head recognition result and the vehicle type recognition result. By adopting the technical scheme, the technical problem that the efficiency and accuracy of identifying the multi-lane vehicle type information are low is solved, and the efficiency and accuracy of identifying the multi-lane vehicle type information are improved.
In one exemplary embodiment, the M is equal to 1, and the vehicle type recognition smart box includes: the side camera service module is used for extracting a video stream corresponding to the vehicle body data acquired by the second camera equipment for analysis.
In practical application, the intelligent box for vehicle type identification can process video stream through the following services: the side camera service (which is equivalent to the side camera service module) is mainly used for streaming and acquiring video stream data from the single-car body camera equipment; transmitting the acquired video stream data to an analyzer engine service for analysis, wherein the analyzer engine service is mainly used for providing an analysis function of a vehicle type recognition algorithm for a vehicle type recognition intelligent box; in addition, the side camera service can also issue device information to the vmr _lite service, wherein the vmr _lite service is mainly used for associating message forwarding and communication functions among various services in the vehicle type recognition intelligent box, so that the accuracy of data is ensured. Further, when the analyzer engine service completes the analysis, the corresponding recognition result is also reported to the vmr _lite service.
In one exemplary embodiment, the vehicle model identification intelligence further comprises: the version identification module is used for adding a mark variable to the virtual machine application corresponding to the vehicle type identification intelligent, wherein the mark variable is used for identifying the version type of the current vehicle type identification intelligent.
In one exemplary embodiment, the vehicle model identification intelligence further comprises: and the compatible module is connected with the version identification module and is used for controlling the virtual machine application to run the application function corresponding to the version type under the condition that the version type of the vehicle type identification intelligent is determined.
That is, in order to ensure compatibility with the old version smart box before, a flag variable can be added to the vmr _lite service to distinguish whether the old version of the vehicle type recognition box before or the new version of the vehicle type recognition box, so that the old version of the function can be compatible with the new version of the vehicle type recognition smart box, and the aim of accessing a vehicle head camera and a vehicle body camera in one smart box can be achieved.
In one exemplary embodiment, the head recognition smart box includes: the network service module is used for respectively setting network channels for N first camera devices connected with the headstock identification intelligent box.
It can be understood that by setting the corresponding network channels, different first camera devices can provide video streams for the head recognition intelligent box at the same time, and the head recognition intelligent box can also be controlled to receive the video stream state of each first camera device, so that the pull flow process is more flexible.
In an exemplary embodiment, the head recognition smart box further includes: and the analyzer module is connected with the network service module and used for carrying out task distribution control on the N first camera devices, wherein the task distribution control is used for analyzing N video streams of the N first camera devices transmitted through the network channel and distributing corresponding target analyzers for each video stream in the N video streams so as to simultaneously analyze the N video streams through the N target analyzers.
In an actual scene, a web service issues a vehicle head recognition task to vmr _lite, an analyzer acquires the issued recognition task from vmr _lite, the analyzer pulls a video stream of a camera through stream to analyze, after a result is detected, the recognition result is sent to a message queue provided by vmr _lite service, and the web service acquires the recognition result from the message queue of vmr _lite to classify and store.
In one exemplary embodiment, the vehicle model identification intelligence further comprises: the buffer memory module is connected with the virtual machine application corresponding to the vehicle type recognition intelligent and is used for storing vehicle type analysis data generated in the virtual machine and receiving and storing vehicle head analysis data transmitted by the vehicle head recognition intelligent box through network connection; and the fusion module is connected with the cache module and used for fusing the vehicle model analysis data and the vehicle head analysis data stored in the cache module to obtain final data of vehicle body and vehicle head configuration.
In the present embodiment, the term "module" or "unit" refers to a computer program or a part of a computer program having a predetermined function, and works together with other relevant parts to achieve a predetermined object, and may be implemented in whole or in part by using software, hardware (such as a processing circuit or a memory), or a combination thereof. Also, a processor (or multiple processors or memories) may be used to implement one or more modules or units. Furthermore, each module or unit may be part of an overall module or unit that incorporates the functionality of the module or unit.
It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present invention is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present invention. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present invention.
Embodiments of the present application also provide a storage medium including a stored program, wherein the program performs the method of any one of the above when run.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store program code for performing the steps of:
s1, analyzing video streams acquired by N connected first camera devices through a head recognition intelligent box, and determining head recognition results corresponding to the video streams acquired by the N first camera devices;
s2, analyzing video streams collected by M connected second camera devices through a vehicle type recognition intelligent box, and determining vehicle type recognition results corresponding to the video streams collected by the M second camera devices; n and M are positive integers, N is greater than 1, and the video stream at least comprises image information of two vehicles;
s3, determining a vehicle recognition result according to the vehicle head recognition result and the vehicle type recognition result.
Embodiments of the present application also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
According to still another aspect of the embodiments of the present application, there is also provided an electronic device for implementing the above-mentioned vehicle charge and discharge management method. The electronic device of the present embodiment is shown in fig. 6, and comprises a memory 802 and a processor 804, the memory 802 storing a computer program, the processor 804 being arranged to execute the steps of any of the method embodiments described above by means of the computer program.
Alternatively, in this embodiment, the electronic apparatus may be located in at least one network device of a plurality of network devices of the computer network.
Alternatively, it will be appreciated by those skilled in the art that the structure shown in fig. 6 is merely illustrative, and the electronic device may be an apparatus including the above-described flash memory. Fig. 6 is not limited to the structure of the electronic device. For example, the electronic device may also include more or fewer components (e.g., network interfaces, etc.) than shown in FIG. 6, or have a different configuration than shown in FIG. 6.
The memory 802 may be configured to store software programs and modules, such as program instructions/modules corresponding to the vehicle charge and discharge management method and apparatus in the embodiments of the present application, and the processor 804 executes the software programs and modules stored in the memory 802, thereby executing various functional applications and data processing, that is, implementing the vehicle charge and discharge management method described above. Memory 802 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 802 may further include memory remotely located relative to processor 804, which may be connected to the terminal via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof. The memory 802 may specifically, but not exclusively, be used for information such as a log containing modeling data. As an example, as shown in fig. 6, the memory 802 may include, but is not limited to, a module in a management device for charging and discharging the vehicle. In addition, other module units in the vehicle charge and discharge management device may be included, but are not limited to, and are not described in detail in this example.
Optionally, the transmission device 806 is used to receive or transmit data via a network. Specific examples of the network described above may include wired networks and wireless networks. In one example, the transmission means 806 includes a network adapter (Network Interface Controller, NIC) that can connect to other network devices and routers via a network cable to communicate with the internet or a local area network. In one example, the transmission device 806 is a Radio Frequency (RF) module for communicating wirelessly with the internet.
In addition, the electronic device further includes: a display 808; and a connection bus 810 for connecting the respective module parts in the above-described electronic device.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.
Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:
s1, analyzing video streams acquired by N connected first camera devices through a head recognition intelligent box, and determining head recognition results corresponding to the video streams acquired by the N first camera devices;
s2, analyzing video streams collected by M connected second camera devices through a vehicle type recognition intelligent box, and determining vehicle type recognition results corresponding to the video streams collected by the M second camera devices; n and M are positive integers, N is greater than 1, and the video stream at least comprises image information of two vehicles;
s3, determining a vehicle recognition result according to the vehicle head recognition result and the vehicle type recognition result.
Alternatively, in the present embodiment, the storage medium may include, but is not limited to: a U-disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Alternatively, specific examples in this embodiment may refer to examples described in the foregoing embodiments and optional implementations, and this embodiment is not described herein.
It will be appreciated by those skilled in the art that the modules or steps of the application described above may be implemented in a general purpose computing device, they may be centralized on a single computing device, or distributed across a network of computing devices, or they may alternatively be implemented in program code executable by computing devices, such that they may be stored in a memory device for execution by the computing devices and, in some cases, the steps shown or described may be performed in a different order than what is shown or described, or they may be implemented as individual integrated circuit modules, or as individual integrated circuit modules. Thus, the present application is not limited to any specific combination of hardware and software.
The foregoing is merely a preferred embodiment of the present application and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present application and are intended to be comprehended within the scope of the present application.
Claims (10)
1. A vehicle identification system, characterized by comprising:
the headstock identification intelligent box is connected with the N first camera devices and is used for analyzing the video streams collected by the N first camera devices to determine headstock identification results corresponding to the video streams collected by the N first camera devices;
the vehicle type recognition intelligent box is connected with the M second camera devices and is used for analyzing video streams collected by the M second camera devices to determine vehicle type recognition results corresponding to the video streams collected by the M second camera devices; n and M are positive integers, N is greater than 1, and the video stream at least comprises image information of two vehicles;
the intelligent vehicle type recognition box is further used for determining a vehicle recognition result according to the vehicle head recognition result and the vehicle type recognition result.
2. The vehicle identification system of claim 1, wherein M is equal to 1, the vehicle model identification smart box comprising: the side camera service module is used for extracting a video stream corresponding to the vehicle body data acquired by the second camera equipment for analysis.
3. The vehicle identification system of claim 1, wherein the vehicle model identification intelligence further comprises: the version identification module is used for adding a mark variable to the virtual machine application corresponding to the vehicle type identification intelligent, wherein the mark variable is used for identifying the version type of the current vehicle type identification intelligent.
4. The vehicle identification system of claim 3, wherein the vehicle model identification intelligence further comprises: and the compatible module is connected with the version identification module and is used for controlling the virtual machine application to run the application function corresponding to the version type under the condition that the version type of the vehicle type identification intelligent is determined.
5. The vehicle identification system of claim 1, wherein the head identification smart box comprises: the network service module is used for respectively setting network channels for N first camera devices connected with the headstock identification intelligent box.
6. The vehicle identification system of claim 5, wherein the head identification smart box further comprises: and the analyzer module is connected with the network service module and used for carrying out task distribution control on the N first camera devices, wherein the task distribution control is used for analyzing N video streams of the N first camera devices transmitted through the network channel and distributing corresponding target analyzers for each video stream in the N video streams so as to simultaneously analyze the N video streams through the N target analyzers.
7. The vehicle identification system of claim 1, wherein the vehicle model identification intelligence further comprises: the buffer memory module is connected with the virtual machine application corresponding to the vehicle type recognition intelligent and is used for storing vehicle type analysis data generated in the virtual machine and receiving and storing vehicle head analysis data transmitted by the vehicle head recognition intelligent box through network connection;
and the fusion module is connected with the cache module and used for fusing the vehicle model analysis data and the vehicle head analysis data stored in the cache module to obtain final data of vehicle body and vehicle head configuration.
8. A vehicle identification method, characterized by comprising:
analyzing video streams collected by N connected first camera devices through a head recognition intelligent box, and determining head recognition results corresponding to the video streams collected by the N first camera devices;
analyzing video streams collected by M connected second camera devices through a vehicle type recognition intelligent box, and determining vehicle type recognition results corresponding to the video streams collected by the M second camera devices; n and M are positive integers, N is greater than 1, and the video stream at least comprises image information of two vehicles;
and determining a vehicle recognition result according to the vehicle head recognition result and the vehicle type recognition result.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored program, wherein the program when run performs the method of claim 8.
10. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method according to claim 8 by means of the computer program.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311849276.2A CN117710908A (en) | 2023-12-28 | 2023-12-28 | Vehicle identification system and method, storage medium and electronic device |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202311849276.2A CN117710908A (en) | 2023-12-28 | 2023-12-28 | Vehicle identification system and method, storage medium and electronic device |
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| CN117710908A true CN117710908A (en) | 2024-03-15 |
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| CN202311849276.2A Pending CN117710908A (en) | 2023-12-28 | 2023-12-28 | Vehicle identification system and method, storage medium and electronic device |
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| CN (1) | CN117710908A (en) |
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